Search results for: Liya Kalinnikova Magnusson

Authors: Liya Kalinnikova Magnusson

Abstract:

The present and ongoing research investigation are focusing on special educational origins in Moldova for children with disabilities and its development towards inclusion. The research is coordinated with related research on inclusion in Ukraine and other countries. The research interest in these issues in Moldova is caused by several reasons. The first one is based upon one of the intensive processes of deconstruction of special education institutions in Moldova since 1989. A large number of children with disabilities have been dropping out of these institutions: from 11400 students in 1989 to 5800 students in 1996, corresponding to 1% of all school-age Moldovan learners. Despite the fact that a huge number of students was integrated into regular schools and the dynamics of this data across the country was uneven (the opposite, the dynamics of exclusion was raised in Trans-Dniester on the border of Moldova), the volume of the change was evident and traditional special educational provision was under stable decline. The second reason is tied to transitional challenges, which Moldova met under the force to economic liberalisation that led the country to poverty. Deinstitutionalization of the entire state system took place in the situation of economic polarization of the society. The level of social benefits was dramatically diminished, increasing inequality. The most vulnerable from the comprehensive income consideration were families with many children, children with disabilities, children with health problems, etc.: each third child belonged to the poorest population. In 2000-2001: 87,4% of all families with children had incomes below the minimum wage. The research question raised based upon these considerations has been addressed to the investigation of particular patterns of the origins of special education and its development towards inclusion in Moldova from 1980 until the present date: what is the pattern of special education origins and what are particular arrangements of special education development towards inclusion against inequality? This is a qualitative study, with relevant peer review resources connected to the research question and national documents of educational reforms towards inclusion retrospectively and contemporary, analysed by a content analysis approach. This study utilises long term statistics completed by the respective international agencies as a result of regular monitoring of the implementation of educational reforms. The main findings were composed in three big themes: adoption of the Soviet pattern of special education, ‘endemic stress’ of breaking the pattern, and ‘paradoxes of resolution’.

Keywords: special education, statistics, educational reforms, inclusion, children with disabilities, content analysis

Procedia PDF Downloads 132

Authors: Liya Shan, Qing Liao, Qinyue Hu, Shantao Jiang, Tao Wang

Abstract:

In this paper, a Quality of Experience (QoE)-driven cross-layer resource allocation scheme for high traffic service over Open Wireless Network (OWN) downlink is proposed, and the related problem about the users in the whole cell including the users in overlap region of different cells has been solved.A method, in which assess models of the BestEffort service and the no-reference assess algorithm for video service are adopted, to calculate the Mean Opinion Score (MOS) value for high traffic service has been introduced. The cross-layer architecture considers the parameters in application layer, media access control layer and physical layer jointly. Based on this architecture and the MOS value, the Binary Constrained Particle Swarm Optimization (B_CPSO) algorithm is used to solve the cross-layer resource allocation problem. In addition,simulationresults show that the proposed scheme significantly outperforms other schemes in terms of maximizing average users’ MOS value for the whole system as well as maintaining fairness among users.

Keywords: high traffic service, cross-layer resource allocation, QoE, B_CPSO, OWN

Procedia PDF Downloads 514

Authors: Leah Ghebreberhan, Liya Abraham, John Issac, Atul Kaushik

Abstract:

Medicinal plants are used for various indications in Eritrea according to traditional systems of medicine. Safety concerns, however, are dubious since some medicinal plants have toxic effects indeed. The medicinal plants under study (Commicarpus pedunculosis, Steganotaenia araliaceae, Boscia angustifolia, Solanum incanum, and Calpurnia aurea) are used in the treatment of various diseases. Thus, safety studies must be performed prior to usage since they are rich in phytoconstituents like saponins. Saponns are natural glycosides with several pharmacologic activities including hemolysis. The study was done to assess the level of saponin and toxic effects (hemolysis) of medicinal plants used in folk medicine. The plant extracts were subject to phytochemical analysis, foam test, and hemolytic assay. Regarding the Fh value, Solanam incanum consisted highest Fh value (20mm), whereas Boscia angustifolia showed the lowest Fh value (10mm). The level of hemolysis of all the plant extracts ranged between 9.0 to 20.2 %. All the plant extracts were suitable for treatment with respect to saponin level since they exhibited minimal hemolytic effect against erythrocytes.

Keywords: Boscia angustifolia, Calpurnia aurea, Commicarpus pedunculosis, hemolysis, saponin, Solanum incanum, Steganotaenia araliaceae

Procedia PDF Downloads 210

Authors: Liya Abraham

Abstract:

Medicinal plants are globally valuable sources of herbal products, either as lifesaving or life maintaining medicines. Studies reveal that more than 25% of modern drugs in the world are derived from plants. The Horn of Africa as a world hotspot; it has more than 1500 endemic plants. Eritrea, a country located in the Horn of Africa, is blessed with medicinal flora and fauna and marine and terrestrial biodiversity. Previous studies of flora of Ethiopia and Eritrea, incomplete species lists, indicate figures ranging between 6000 and 7000 species, with levels of endemism between 12–20%. In the past two decades, there has been growing interest in natural remedy herbal medicines owing to, but not limited to; resistance to antimicrobials, intolerance of side effects of modern drugs, and rise in chronic diseases like diabetes, hypertension, cancer, etc. Hence, owing to the rising demand for nature based health solutions, deforestation, construction purposes, grazing, and agricultural expansion; several medicinal plants in general and the endemic ones, in particular, are in the verge of extinction. Therefore, conservation strategies of endangered and endemic medicinal plants, especially those located in hot spot regions, must be promoted at global level. Thus, the author aims to share certain information regarding the endemic medicinal plants in Eritrea with the international scientific world.

Keywords: endemic, eritrea, horn of Africa, medicinal plants, species

Procedia PDF Downloads 132

Authors: Liya Abraham

Abstract:

Eritrea is located along the Red Sea, north of the Horn of Africa, between Djibouti and Sudan and has a population of about 3.2 million as of 2010. It has six administrative regions; Anseba, Debub, Debubawi K’eyih Bahri, Gash-Barka, Ma'akel, and Semenawi K’eyih Bahri. Eritrea has got its independence in 1991 after 30 years war of liberation. The country is blessed with various medicinal flora and fauna, and marine and terrestrial biodiversity. Traditional Medicine (TM) has been an integral part of the Eritrean culture for centuries. So far, more than 19 TM modalities have been recognized, and are broadly categorized as; herbal, procedure-based and spiritual. Despite the availability of modern medicine to the majority of the population, TM is still widely practiced. The rationale behind widespread use is accessibility, affordability and cultural acceptability. Hence, TM is of great contribution to the Eritrean health care system. As a matter of fact, harnessing the potential contribution of effective and safe TM in order to attain Universal Health Coverage (UHC) has been emphasized in the WHO TM strategy 2014-2023. The Eritrean TM, however, was operating without regulation and reliable scientific justification behind its safety and efficacy. Thus, the Ministry of Health (MoH), in recognition of the role of TM in primary healthcare and safeguard public health, established a regulatory body for TM so-called as Traditional Medicine Unit (TMU) in 2012. The mission of the unit is to ensure rational TM use through an integrated health service delivery system and contribute to the country’s economic and social development. The unit has established its national TM policy in 2017. The activities of the unit are guided by the National TM Advisory Committee (TMAC), responsible for the provision of technical assistance and advisory role. Moreover, the Legal Framework and Code of Ethics and Practice which provide a legal basis for the regulation of TM have also been drafted. In recognition of the importance of TM research and development, the unit launched a nationwide TM survey in 2017 and had surveyed two zones (Gash-Barka and Debub). The findings of the survey were subjected to a research dissemination workshop and publication in international journals. Furthermore, TM-related adverse events reporting tool (Green Form) aiming to guide regulatory interventions and researches have been established by the unit, and ever since reports are flowing. The unit has also been offering training to THPs, pharmacy students and health care professionals regarding TM and its regulatory activities. In addition, as part of the establishment of the national medicinal plants' database and herbal monograph, more than 329 and 30 medicinal plants, have been compiled respectively. In conclusion, TM is still widely accepted and practiced in Eritrea. The TMU ever since its establishment is endeavoring to ensure the safety and efficacy of the TM, and its integration in the mainstream health service delivery system.

Keywords: efficacy, regulation, safety, traditional medicine, traditional medicine unit, universal health coverage

Procedia PDF Downloads 147

Authors: Mingxin Li, Liya Ni

Abstract:

Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

Procedia PDF Downloads 100